Summery The high degree of uncertainty when working with process operational uncertainties (e.g. daily fluctuations, seasonal variations in production levels) and physical property uncertainties adds complexity to this already challenging chemical process design problem. A flexibility analysis is to determine the maximum parameter range that a design can tolerate for feasible operation. It is one of important fact of chemical process design in terms of safety and cost. Although some of researcher had suggested methodologies for successfully solving this mixed integer nonlinear programming, it is still a challenging task to find critical point and guarantee the global solution when it is non-convex problem. In this presentation, we will develop a new evolutionary algorithm to solve the flexibility index problem with help of geometry properties to the constraint. The advantages of the novel approach for obtaining the flexibility index and critical points will be demonstrated.

Methodology A new robust method, based on combined stochastic method and line search for solving flexibility index problem under uncertainty is suggested in this presentation. Evolutionary algorithm is used for finding critical point in reduced space, and the line search is used for formulating reduced space. We establish a new framework for obtaining worst scenario (critical point) using evolutionary algorithm with line search. This method can be applied to any case regardless of convexity of given constraint functions. In this presentation, several examples-heat exchanger, CSTR and pipe and pump etc, solved using our new method will be discussed. And the advantages and the disadvantages of our method will be presented.

Significance This presentation proposes new approach for finding flexibility index problem without trapping into MINLP. Stochastic method and a novel line search enable to reduce dramatically computational search space. The proposed approach brings one more option to solve the flexibility index problem, especially for the nonlinear constraints.

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